OpenCV_4.2.0/opencv_contrib-4.2.0/modules/text/test/test_detection.cpp

92 lines
3.0 KiB
C++

// This file is part of OpenCV project.
// It is subject to the license terms in the LICENSE file found in the top-level directory
// of this distribution and at http://opencv.org/license.html.
#include "test_precomp.hpp"
#include "opencv2/imgcodecs.hpp"
namespace opencv_test { namespace {
// Just skip test in case of missed testdata
static cv::String findDataFile(const String& path)
{
return cvtest::findDataFile(path, false);
}
PARAM_TEST_CASE(Detection, std::string, bool)
{
Ptr<ERFilter> er_filter1;
Ptr<ERFilter> er_filter2;
// SetUp doesn't handle SkipTestException
void InitERFilter()
{
String nm1_file = findDataFile("trained_classifierNM1.xml");
String nm2_file = findDataFile("trained_classifierNM2.xml");
// Create ERFilter objects with the 1st and 2nd stage default classifiers
er_filter1 = createERFilterNM1(loadClassifierNM1(nm1_file),16,0.00015f,0.13f,0.2f,true,0.1f);
er_filter2 = createERFilterNM2(loadClassifierNM2(nm2_file),0.5);
}
};
TEST_P(Detection, sample)
{
InitERFilter();
std::string imageName = GET_PARAM(0);
bool anyDirection = GET_PARAM(1);
if (anyDirection)
throw SkipTestException("ERGROUPING_ORIENTATION_ANY mode is not supported");
std::cout << "Image: " << imageName << std::endl;
std::cout << "Orientation: " << (anyDirection ? "any" : "horiz") << std::endl;
Mat src = cv::imread(findDataFile(imageName));
ASSERT_FALSE(src.empty());
// Extract channels to be processed individually
std::vector<Mat> channels;
computeNMChannels(src, channels);
// Append negative channels to detect ER- (bright regions over dark background)
for (size_t c = channels.size(); c > 0; c--)
channels.push_back(255 - channels[c - 1]);
std::vector<std::vector<ERStat> > regions(channels.size());
// Apply the default cascade classifier to each independent channel (could be done in parallel)
for (size_t c = 0; c < channels.size(); c++)
{
er_filter1->run(channels[c], regions[c]);
er_filter2->run(channels[c], regions[c]);
}
// Detect character groups
std::vector< std::vector<Vec2i> > region_groups;
std::vector<Rect> groups_boxes;
if (!anyDirection)
erGrouping(src, channels, regions, region_groups, groups_boxes, ERGROUPING_ORIENTATION_HORIZ);
else
erGrouping(src, channels, regions, region_groups, groups_boxes, ERGROUPING_ORIENTATION_ANY,
findDataFile("trained_classifier_erGrouping.xml"), 0.5);
std::cout << "Found groups: " << groups_boxes.size() << std::endl;
EXPECT_GT(groups_boxes.size(), 3u);
}
INSTANTIATE_TEST_CASE_P(Text, Detection,
testing::Combine(
testing::Values(
"text/scenetext01.jpg",
"text/scenetext02.jpg",
"text/scenetext03.jpg",
"text/scenetext04.jpg",
"text/scenetext05.jpg",
"text/scenetext06.jpg"
),
testing::Bool()
));
}} // namespace